The most scalable big data platform on the planet
Combining a range of powerful open-source and in-house solutions,
Gruter Big Data Platform is a revolutionary and fully-scalable big data platform
based on Hadoop and the Hadoop ecosystem of technologies.
Data management handles control each step of the
data life cycle from harvesting, storage and analysis,
Scales to meet data flow requirements without system
or service interruption.
User-friendly web UI and management console simplifies
queries in distributed environments.
High scalability and open-source components on x86
machines support low-cost builds and conserve capital.
Data replication and redundancy give robustness to data
and meta-data processing.
Modular design enables components to be modified
to suit local requirements.
Distributed architecture facilitates maximum throughput
across the system.
Integrates the latest technologies into the Hadoop
ecosystem ensuring optimal performance.
Gruter Big Data Platform Architecture
Time And Cost Savings
Gruter Big Data Platform is a proven platform born of Gruter's many years of data system development and management experience. Carefully designed to be fast, powerful, efficient and cost-effective, Gruter Big Data Platform gives you the system you need at the right price without sacrificing performance. As a pre-packaged working system, installation and configuration is all that is required to have your own big data system up and running and meeting your computing requirements. What’s more, the system utilizes x86 commodity machines and open-source software components, giving the platform a familiar feel at an affordable cost.
Working hard in the field since 2006
Gruter has partnered with many clients including Samsung to design, build and manage big data systems based on our in-house platform. Operating Hadoop clusters since 2006, Gruter has worked hard to optimize the platform to ensure every advantage and cost saving has been integrated into a single high-performance unit without sacrificing the flexibility needed for wide-ranging applications.
Field Case 1Recommendation system for shopping mall or advertising system
Imagine you want to build a high performance recommendation system for a major e-commerce property. The recommendation system requires ongoing improvements and tweaks based on predetermined algorithms and user analytics. After running a few calculations on your model it quickly becomes apparent that the volume of real-time transactions, web log data and user information you need to handle to implement your recommendation model is enormous. Bigger numbers than you’ve seen a traditional system handle before. You quickly realize you need a new generation data system specifically constructed to process numbers that big. You turn to Gruter Big Data Platform to help you find, extract and generate a training data set containing near real-time user trends across tens of millions of transactions per hour.
Field Case 2Abnormal Transaction and Fraud Detection Security System
Imagine you want to build a security system to detect attacks or attempted attacks on your system and applications. As your applications and domains vary and are highly distributed, collecting and analyzing data from such a complex computing environment is the first challenge you face. Running analyses on huge volumes of incoming data in real-time or near real-time is the second major challenge you have to deal with. You turn to Gruter Big Data Platform because it enables you to gather data from hundreds of distributed servers and allows you to run analyses at three time settings: real-time, near real-time and batch.
Field Case 3Extraction Transformation Loading (ETL) for existing Business Information System
Your business is growing and you have explosively increasing data from your production line sensors. Your existing ETL and BI solutions have performed well until recent months. Faced with capacity limitations, exponential scale-out costs and costly downtime, you realize that you’ve hit a snag. Your turn to Gruter Big Data Platform because it scales with minimum downtime and provides a seamless and cost-effective move to expanded capacity thanks to the scalability of its Hadoop architecture and clever design based on the use of commodity x86 machines and open-source software.